Random Leader Election in Distributed Networks
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Solution Overview
Problem
Current random leader election algorithms in distributed networks are vulnerable to adversarial attacks and lack sufficient randomness, making it easy for adversaries to manipulate the leader election process, and they do not effectively distribute randomness among all processes.
Innovation Solution
A computer-implemented method where each running process generates and shares random information, which is then transformed using shared functions to create distributed random information, allowing each process to autonomously elect a leader in one communication round, ensuring high randomness and preventing manipulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current random leader election algorithms are used, then the leader election process can be completed, but the randomness is insufficient and vulnerable to adversarial attacks
Solution Approach 1:
The algorithm segments the leader election process into distinct phases: random value generation by each process, collection of random values from all processes, and deterministic leader selection based on the collected randomness. This segmentation ensures that no single process controls the entire election, preventing adversarial manipulation while maintaining security.
2Reliability
If traditional leader election algorithms are used, then the election can proceed, but the randomness distribution among processes is inadequate
Solution Approach 1:
The algorithm merges the random value generation from all processes into a collective random state that is then used by every process for leader selection. This merging ensures uniform randomness distribution across all processes while the deterministic selection function keeps the algorithm complexity manageable.
3Reliability
If a quorum-based system is implemented, then fault tolerance is improved, but the system complexity increases
Solution Approach 1:
The algorithm performs preliminary random value generation and collection before the actual leader selection. By preparing the random state in advance and making it available to all processes, the system achieves fault tolerance without requiring complex real-time coordination during the election itself.
Data Source
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AI summary
A computer-implemented method for the random-based leader election in a distributed network of data processing devices, said distributed network comprising a plurality of identified asynchronous processes, wherein all said identified processes or a subset thereof are running processes participating in the leader election, comprising the following steps: a) a random information (r) is generated by each running process and shared with the other running processes, so that each running process maintains a set of said random information (r), (Anm: = one round) b) a distributed random information (R) is calculated by each running process from the set of random information (r) by applying a first shared transformation function (f1), so that the same distributed random information (R) is made available to each running process, c) a designator of a single one of said running processes is calculated from the distributed random information (R) by means of a second shared transformation function (f2), d) a leader is elected among said running processes based on said designator.